title: Predicting functional gene interactions with the hierarchical interaction score.
abstract: Systems biology aims to unravel the vast network of functional interactions that govern biological systems. To date, the inference of gene interactions from large-scale 'omics data is typically achieved using correlations. We present the hierarchical interaction score (HIS) and show that the HIS outperforms commonly used methods in the inference of functional interactions between genes measured in large-scale experiments, making it a valuable statistic for systems biology.
authors.affiliation: 1] Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland. [2].
authors.forename: Berend
authors.initials: B
authors.lastname: Snijder
authors.forename: Prisca
authors.initials: P
authors.lastname: Liberali
authors.forename: Mathieu
authors.initials: M
authors.lastname: Frechin
authors.forename: Thomas
authors.initials: T
authors.lastname: Stoeger
authors.forename: Lucas
authors.initials: L
authors.lastname: Pelkmans
mesh_terms: D000890:Anti-Infective Agents / Q000494:pharmacology; D004843:Epistasis, Genetic; D004926:Escherichia coli / Q000187:drug effects / Q000235:genetics; D008826:Microbial Sensitivity Tests; D012441:Saccharomyces cerevisiae / Q000187:drug effects / Q000235:genetics; D049490:Systems Biology
chemical_list: D000890:Anti-Infective Agents